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Lavaei Department of Electrical Engineering Columbia University Joint work with Somayeh Sojoudi Convexification of Optimal Power Flow Problem by Means of Phase Shifters Power Networks ID: 400677

university javad lavaei columbia javad university columbia lavaei phase shifters power opf bus voltage flow network work project networks

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Slide1

Javad LavaeiDepartment of Electrical EngineeringColumbia UniversityJoint work with Somayeh Sojoudi

Convexification of Optimal Power Flow Problem by Means of Phase ShiftersSlide2

Power Networks

Optimizations: Optimal power flow (OPF) Security-constrained OPF State estimation Network reconfiguration Unit commitment

Dynamic energy management

Issue of non-convexity:

Discrete parameters

Nonlinearity in continuous variables

Transition from traditional grid to smart grid: More variables (10X) Time constraints (100X)

Javad Lavaei, Columbia University

2Slide3

Broad Interest in Optimal Power FlowJavad Lavaei, Columbia University3 OPF-based problems solved on different time scales:

Electricity marketReal-time operationSecurity assessmentTransmission planning Existing methods based on linearization or local search

Question:

How to find the best solution using a scalable robust algorithm?

Huge literature since 1962 by power, OR and Econ people

Slide4

Summary of ResultsJavad Lavaei, Columbia University4 A sufficient condition to globally solve OPF:

Numerous randomly generated systems IEEE systems with 14, 30, 57, 118, 300 buses European grid Various theories: It holds widely in practice

Project 1:

How to solve a given OPF in polynomial time?

(joint work with Steven Low)

Distribution networks are fine (under certain assumptions).

Every transmission network can be turned into a good one

(under

assumptions

).

Project 2:

Find network topologies over which optimization is easy?

(joint work with Somayeh Sojoudi, David Tse and Baosen Zhang)

Slide5

Summary of ResultsJavad Lavaei, Columbia University5Project 3:

How to design a distributed algorithm for solving OPF? (joint work with Stephen Boyd, Eric Chu and Matt Kranning) A practical (infinitely) parallelizable algorithm It solves 10,000-bus OPF in 0.85 seconds on a single core machine.

Project 4:

How to do optimization for mesh networks?

(joint work with

Ramtin

Madani and Somayeh Sojoudi)

Developed a penalization technique

Verified its performance on IEEE systems with 7000 cost functions

Focus of this talk:

Revisit Project 2 and remove its assumptionsSlide6

Geometric Intuition: Two-Generator Network

Javad Lavaei, Columbia University

6Slide7

Optimal Power FlowCost OperationFlowBalance

SDP relaxation:

Remove the rank constraint.

Exactness of relaxation:

We study it thru a geometric approach.

Javad Lavaei, Columbia University

7Slide8

Acyclic Three-Bus Networks

Assume

that the voltage magnitude is fixed at every bus.

Javad Lavaei, Columbia University

8Slide9

Geometric Interpretation

(+,+)

Pareto face:

Pareto face

Convex Pareto Front:

Injection region and its convex hull share the same front.

Javad Lavaei, Columbia University

9Slide10

Two-Bus Network Two-bus network with power constraints:

P

1

P

2

P

1

P

2

P

1

P

2

P

1

P

2

P

1

P

2

P

1

P

2

Javad Lavaei, Columbia University

10Slide11

General Tree Network Assume that each flow-restricted region is already Pareto (monotonic curve):

PijPji

Ratio from 1 to 10:

Max angle from 45

o

to 80

o

Javad Lavaei, Columbia University

11Slide12

Three-Bus Networks Issues: Coupling thru angles and voltage magnitudes

Variable voltage magnitude:

Javad Lavaei, Columbia University

12Slide13

Decoupling Angles Phase shifter: An ideal transformer changing a phase Phase shifter kills the angles coupling.

PS

Javad Lavaei, Columbia University

13Slide14

Decoupling Voltage Magnitudes Define:

Boundary

Javad Lavaei, Columbia University

14Slide15

Injection & Flow Regions Voltage coupling introduces linear equations in a high-dimensional space.

Line (i,j):

Javad Lavaei, Columbia University

15Slide16

Main Result Current practice in power systems:Tight voltage magnitudes.Not too large angle differences.

Adding virtual phase shifters is often the only relaxation needed in practice.

Javad Lavaei, Columbia University

16Slide17

Phase ShiftersJavad Lavaei, Columbia University17

Blue:

F

easible set (P

G1

,P

G2

)

Green:

Effect of phase shifter

Red:

Effect of convexification

Minimization over green = Minimization over green and red (even with box constraints)Slide18

Phase ShiftersSimulations: Zero duality gap for IEEE 30-bus system Guarantee zero duality gap for all possible load profiles? Theoretical side: Add 12 phase shifters Practical side: 2 phase shifters are enough

IEEE 118-bus system needs no phase shifters (power loss case)

Javad Lavaei, Columbia University

18

Phase shifters speed up the computation:Slide19

ConclusionsFocus: OPF with a 50-year historyGoal: Find a near-global solution efficiently

Main result: Virtual phase shifters make OPF easy under tight voltage magnitudes and not too loose angle differences. Future work: How to lessen the effect of virtual phase shifters?

Javad Lavaei, Columbia University

19